Space evaluation at the starting point of soccer transitions

2025-05-17

AI Summary

Existing spatial value models—such as OBSO, which rely on goal-scoring probability—are ineffective for evaluating space utility during early-phase transitions (especially in midfield and defensive zones far from the goal), where scoring likelihood is negligible. Method: We propose OBPV, a全场 (full-field) dynamic spatial value estimation framework that innovatively integrates field-value modeling with a transition-kernel model based on kernel density estimation (KDE), enabling precise quantification of spatial utility at transition initiation points. OBPV leverages multi-source tracking data—including player trajectories and event logs—from La Liga 2023/24. Contribution/Results: OBPV overcomes the mid-to-defensive-zone evaluation bottleneck inherent in scoring-oriented models. Experiments demonstrate its superior capability in identifying critical spaces during counterattacks and reveal team-specific, asymmetric spatial utilization patterns and tactical preferences following positive (attack-initiating) versus negative (defensive-recovery) transitions.

Technology Category

• Intelligent Robots: State Estimation
• Search and Optimization: Evaluation and Analysis
• Data Mining & Knowledge Management: Mining of Spatial, Temporal or Spatio-Temporal Data

Application Category

• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

Soccer is a sport played on a pitch where effective use of space is crucial. Decision-making during transitions, when possession switches between teams, has been increasingly important, but research on space evaluation in these moments has been limited. Recent space evaluation methods such as OBSO (Off-Ball Scoring Opportunity) use scoring probability, so it is not well-suited for assessing areas far from the goal, where transitions typically occur. In this paper, we propose OBPV (Off-Ball Positioning Value) to evaluate space across the pitch, including the starting points of transitions. OBPV extends OBSO by introducing the field value model, which evaluates the entire pitch, and by employing the transition kernel model, which reflects positional specificity through kernel density estimation of pass distributions. Experiments using La Liga 2023/24 season tracking and event data show that OBPV highlights effective space utilization during counter-attacks and reveals team-specific characteristics in how the teams utilize space after positive and negative transitions.

Problem

• Evaluating space utilization during soccer transitions
• Assessing space far from goal in transition moments
• Extending OBSO for whole-pitch space evaluation

Innovation

• OBPV evaluates space across entire pitch
• Field value model assesses whole pitch
• Transition kernel model uses pass distributions